Guest Column | March 11, 2024

Getting To Know MAM, The New Quality Control Strategy On the Block

By Diane McCarthy and Li Jing, United States Pharmacopeia

Pharmaceutical scientific researchers GettyImages-586052980

Proteins, including recombinant proteins developed for therapeutic applications, can be complex molecules, and a single preparation of protein can be heterogenous. They may contain many amino acid residues that are subject to post-translational modifications (PTM) or degradation in aqueous solutions. This complexity can result in a high level of size, charge, and glycan heterogeneity even within a single preparation of the protein, which may affect the safety and efficacy of the drug product.

To mitigate the risks associated with protein modifications, it is crucial to characterize the product quality attributes (PQAs) during development and monitor critical quality attributes (CQAs) for quality control purposes throughout the life cycle of the protein product. One emerging strategy, the multi-attribute method (MAM), offers a one-stop shop for analysis, and in this two-part series, we’ll offer an overview of MAM, technical considerations for its implementation, and its applications in process development and quality control (QC).

Later, in part 2 of this series, we’ll highlight the standards and scientific content provided by the United States Pharmacopeia (USP) to support the adoption of this powerful method, including a new General Chapter <1060> in the United States Pharmacopeia-National Formulary (USP-NF) titled Mass Spectrometry Based Multi-Attribute Method for Therapeutic Proteins.

Characterization of PQAs and CQAs is traditionally done using various chromatographic and electrophoretic assays. These may include capillary electrophoresis-sodium dodecyl sulfate (CE-SDS) and size-exclusion chromatography (SEC) for purity and size variant analysis, capillary isoelectric focusing (cIEF), imaged capillary isoelectric focusing (icIEF), or ion exchange chromatography (IEX) for charge variant analysis, and hydrophilic interaction liquid chromatography (HILIC) for glycan analysis.

However, these conventional analytical methods have limitations. Some product-related substances and impurities cannot be separated or detected using these methods. Moreover, these assays may provide only indirect measurements of biologically relevant quality attributes. They often fail to identify the specific location or criticality of modifications.

As a result, multiple orthogonal methods are often required for process and formulation development, batch release, and stability analysis. This approach can be time-consuming, expensive, and resource intensive. Furthermore, the use of multiple methods to determine CQAs risks introducing multiple sources of error into the analysis.

Now Comes The Multi-Attribute Method

MAM, which is based on liquid chromatography and mass spectrometry (LC-MS), is designed to simultaneously detect, identify, quantify, and monitor multiple PQAs and CQAs. These attributes include sequence anomalies, PTMs, and product-related impurities that can occur in a protein. Implementing MAM can result in a better understanding of the product and process, shorter development timelines, and improved control strategies focused on specific CQAs.

MAM utilizes the specificity of MS to assess multiple quality attributes at the amino acid level. It can replace multiple traditional methods, such as peptide mapping, glycan analysis, capillary electrophoresis, and IEX, and enable the detection of unexpected modifications that may not be as readily detected using traditional analytical methods.

MS is routinely being used as an analytical method in the biopharmaceutical industry and is increasingly being used in GMP QC laboratories. Retrospective analyses have been published on the use of MS in the characterization section of therapeutic protein Biological License Applications (BLAs) that were approved between 2000 and 2015, as well as between 2016 and 2020. The first study showed that MS was used in 79 out of the 80 assessed BLAs.1 The more recent study found that MS was used in all 93 BLAs (65 new drugs and 28 biosimilars) approved between 2016 and 2020.2

Overall, the studies found an increase in MS usage over time, both in the number of BLAs per year and in the number of workflows and attributes analyzed by MS within the BLAs. The top eight quality attributes most commonly assessed by MS were amino acid sequence, molecular mass, oxidation, disulfide bonds, deamidation, glycosylation, N-terminal sequence variants, and C-terminal sequence variants. These attributes remained consistent when compared to BLAs approved during the earlier time period.

Multi-Attribute Methods

Introduced in 2015, MAM enables the simultaneous measurement of multiple protein modifications in a single MS run.3 It is a sensitive and high-resolution approach that can replace multiple chromatographic and electrophoretic assays.

MAM provides enhanced attribute information during process development and is increasingly being used for cGMP release and stability testing. It follows quality by design (QbD) principles and can be used for in-line monitoring, as well as a process analytical technology (PAT) tool during both clinical and commercial manufacturing.

MAM differs from conventional LC-MS, which has been used for characterization in the biopharmaceutical industry for many years. MAM consists of two distinct phases: a characterization phase and a monitoring phase (Figure 1). In both phases, the therapeutic protein samples are denatured and then digested with a proteolytic enzyme, such as trypsin. The resulting peptides are separated using chromatography and then detected using MS.

Figure 1. Therapeutic proteins, including mAbs, are enzymatically digested into peptide fragments. For characterization, the peptides are analyzed using LC-MS/MS and the acquired data is used for peptide mapping and analysis of any modifications. This analysis is then used for identification of PQAs for routine monitoring. Some of the PQAs that can be monitored for mAbs are 1) glycosylation, 2) N-terminal peptide, 3) oxidation, 4) C-terminal lysine, 5) deamidation, and 6) charge variants. For monitoring, data is acquired by MS and a targeted analysis is performed. The intensity of peptides, both with and without modifications, is measured. Also, NPD can be used to identify new modifications. With NPD, MS data are compared to a reference sample to detect any new ion peaks that may represent a new variation in a quality attribute.

During the initial characterization stage of MAM method development, peptides are analyzed by the mass spectrometer in both MS and tandem MS (MS/MS) modes. The modifications and their locations in the peptide sequence are identified by searching the protein database using the MS/MS data. Size variations from the expected peptides can be indicative of modifications to the protein. Modifications that affect the pharmacological properties and stability of the therapeutic protein are categorized as PQAs.

During the monitoring phase of MAM, a more focused approach is employed to quantify the relative abundance of each PQA within the protein preparation or batch. This is done by measuring the MS ion intensity of peptides with and without modifications. The mass peak areas of both modified and unmodified peptides are obtained from the extracted ion chromatogram (XIC) peak areas. The relative abundance of a PQA is calculated as the percentage of the modified peptide compared to the total mass peak area of both modified and unmodified peptides. This can also be helpful when optimizing the expression conditions for a protein by allowing the comprehensive monitoring of multiple PQAs during process development.

The monitoring phase is focused primarily on previously identified PQAs. However, new peak detection (NPD) is critical for identifying new modifications that may occur over the life cycle of the product. With NPD, MS data are compared to a reference sample to detect any new ion peaks that may represent a new variation in a quality attribute (e.g., a change in the protein that may occur following a change in supplier for a certain reagent). To determine the identity of the new species, the sample can be re-analyzed, and the unknown species can be specifically selected for MS/MS data acquisition. With conventional methods, analysis of new modifications is typically performed manually by a trained analyst using visual comparison of data. However, the exact identities of changes observed are difficult to ascertain due to the limited resolution of conventional methods. In contrast, the MAM NPD workflow can detect new species automatically by comparing mass signal data in the three-dimensional space of retention time, mass to charge ratio (m/z), and intensity, and additional MS/MS analysis can be performed to determine the molecular identify of the new peak.

Comparison Of MAM To Conventional Methods

Table 1 summarizes the capabilities of MAM to detect common quality attributes of monoclonal antibodies (mAbs) compared to conventional methods. In addition to the PQAs listed in Table 1, other modifications such as isomerization, phosphorylation, sulfation, and acetylation may also be analyzed by MAM.

Table 1. Comparison of MAM and conventional analytical methods for measurement of common PQAs. Key: “+” application is used; “-” application not commonly used; “+/-” application may be used. The disulfide isoforms and unpaired cysteines would need to be measured from a peptide map generated from a non-reduced protein sample, as they involve structural features that do not persist or cannot be distinguished upon reduction. This table is adapted from USP-NF General Chapter <1060> Mass Spectrometry Based Multi-Attribute Method for Therapeutic Proteins.

Advantages For Process Development And Quality Control

MAM offers important advantages for both process development and quality control, such as:

  • significantly more information, higher accuracy, higher sensitivity, and very high specificity in a single analysis,
  • amino acid level monitoring and control of CQAs, enabling more detailed understanding and assessment of quality of pharmaceutical products,
  • more meaningful product specifications, allowing process developers to focus only on control of the high-risk attributes of the product,
  • a more detailed view of the impact of process changes, empowering process scientists to fine-tune parameters earlier in development and minimize the requirement for process changes at later stages, which are much more costly,
  • more robust QbD by providing a more thorough and detailed understanding of CQAs and how they are related to changes in the process, and
  • the opportunity to replace multiple analytical methods currently used for process development and release and stability testing, streamlining the laboratory workflows and reducing costs and labor requirements.

Part 2 of this series will explore key factors that can influence the variability of the method, including sample preparation and establishment of system readiness or system suitability. It will also dig into considerations for incorporating MAM into the QC production environment.


  1. Rogstad S., Faustino A., Ruth A., Keire D., Boyne M., Park, J. A. (2017) Retrospective Evaluation of the Use of Mass Spectrometry in FDA Biologics License Applications. J. Am. Soc. Mass Spectrom. 28(5), 786−794
  2. Mans J., Oyugi M., Asmelash B., Sommers C., Rogstad S. (2023) The Use of Mass Spectrometry in Therapeutic Protein Biologics License Applications: A Retrospective Review Revisited. J. Am. Soc. Mass Spectrom. 34 (11), 2575-2584
  3. Rogers R.S., Nightlinger N.S., Livingston B., Campbell P., Bailey R., Balland A. (2015) Development of a Quantitative Mass Spectrometry Multi-attribute Method for Characterization, Quality Control Testing and Disposition of Biologics. MAbs. 7(5):881-90.

About The Authors:

Diane McCarthy, Ph.D., is senior director, science and standards in USP’s Global Biologics Department, where she leads development and maintenance of standards and tools to support quality of medicines and oversees the USP biologics laboratories in the U.S. and India. Her team supports standards and tools across a diverse range of therapies, including vaccines, peptides, cell and gene therapy, monoclonal antibodies, and other protein therapeutics. Prior to joining USP, Diane worked for several small CROs that focused on the use of mass spectrometry for characterization of biologics, host cell proteins, and biomarkers. McCarthy earned her Ph.D. in biochemistry from the University of Texas at Austin.


Li Jing, Ph.D., is a senior manager in USP’s Global Biologics Department, where she  leads a team working with the USP expert committees and multiple expert panels for proteins, peptides, and carbohydrates to develop standards that support biopharmaceutical quality assessment and development. Recently, Jing worked with the USP MAM Expert Panel and developed General Chapter <1060> Mass Spectrometry Based Multi-Attribute Method for Therapeutic Proteins. Jing holds a Ph.D. in analytical chemistry from the University of Georgia and a B.S. in chemistry from Fudan University. She has worked for several biotechnology and pharmaceutical companies, focusing on the development of protein therapeutics and vaccine candidates.